It is known to use computed tomography (CT) based explosive detection systems (EDS) to detect the presence of contraband. As used herein, the term “contraband” refers to any goods, such as an object and/or a material, that are unauthorized to possess, including, but not limited to including, explosives, weapons, drugs, and/or controlled substances. In the embodiments described herein and in the known EDS discussed herein, contraband is contained within a container, such as, but not limited to, a cargo container, a bag, a box, baggage, luggage, a carton, a crate, and/or any other suitable receptacle.
At least some known EDS CT systems acquire a number of two-dimensional (2D) image slices through a container, and analyze each 2D image slice. As is known, each 2D image slice is formed from a rectangular array of picture elements, or pixels. The numeric value of each pixel represents a CT number, which is an estimate of density. As used herein, a CT number is used as an estimate of density of a material, although the CT number is an indication of an attenuation coefficient of the material rather than being a measure of the density of the material. In at least some known analysis methods, the analysis of each image slice includes segmenting, or grouping together, contiguous pixels into regions. Regions within the different 2D image slices are then compared and grouped into image objects representing physical objects within the container. In at least one known 2D image analysis method, there are only a few 2D image slices, and as little as one 2D image slice, through each physical object, making a determination of the presence of a contained volume within the physical object substantially impossible and/or impractical. Accordingly, there is a need for an image analysis method that determines whether a region completely surrounds an area within an image to indicate the presence of a contained volume within an object.
At least some other known EDS CT systems generate full volume data, which includes a large number of cross-sectional 2D image slices. The 2D image slices are generally evenly and closely spaced such that an entire volume of the container is represented. As is known, the volume is represented in the volume data by volume elements, or voxels. The numeric value of each voxel is a CT number. Similar to the 2D image analysis method, during at least one known three-dimensional (3D) image analysis of the volume data, contiguous voxels with a similar CT number are grouped together into image objects that represent characteristics, such as a size, a shape, and an approximate density, of a physical object within the container. Rules are applied to the measurements of the image object, such as a density, a volume, a mass, and/or a shape, to determine if the physical object is contraband and/or another item of interest.
To perform at least some known image analysis methods for the detection of explosives, it is assumed that explosives generally have a characteristic density that often enables explosives to be identified by mass and density. Some such explosives are referred to herein as “standard density explosives.” At least some known benign objects have substantially the same mass and the same density as standard density explosives, so at least some known EDSs will generate an alarm on such benign objects. An alarm on a benign object is called a “false alarm.” Performing an examination for each false alarm may cost time and/or money because at least one known examination is performed on the object by opening a container containing the object and/or by using alternate technologies. In at least some known EDSs, there are a reasonably low number of such types of false alarms because there are only a limited number of benign objects, which may be included in passenger baggage, that have the substantially the same density as an explosive.
However, at least some known explosives, such as powders, are less dense than other known explosives, such as standard density explosives. Such less dense explosives are referred to herein as “low-density explosives.” A need exists for an analysis method that can analyze standard density explosives and low-density explosives to facilitate decreasing a number of false alarms and/or determine if a low-density explosive is contained within a containment vessel.
Further, if an area of a CT image slice is surrounded by a dense material, the CT numbers of the contained area may be inaccurate for various reasons, causing the CT number to generally be higher than if the contained area were not surrounded by a dense material. As such, the measured CT number of some higher density contraband, such as explosives, that is contained in a dense containment vessel may be higher than if the higher density contraband were not in a dense containment vessel. As referred to herein, a “dense containment vessel” is any containment vessel of sufficient density to cause inaccuracies in determining the density of a material within the containment vessel. An example of a dense containment vessel is a metal pipe, such as a steel pipe, a nickel pipe, an iron pipe, a copper pipe, and/or a bronze pipe, a metal container, and/or any other container formed from a relatively high density material. In at least some known EDS CT systems, the higher measured CT number may be higher than the CT number threshold set for contraband, and therefore an alarm may not be generated. However, if a higher threshold is applied to all objects in the container, the false alarm rate would increase. Accordingly, there is a need to determine whether contraband is contained within a dense containment vessel.